hgm
Holonomic Gradient Method and Gradient Descent
The holonomic gradient method (HGM, hgm) gives a way to evaluate normalization constants of unnormalized probability distributions by utilizing holonomic systems of differential or difference equations. The holonomic gradient descent (HGD, hgd) gives a method to find maximal likelihood estimates by utilizing the HGM.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.23 |
rolling source/ R- | hgm_1.23.tar.gz |
92.3 KiB |
1.23 |
rolling linux/jammy R-4.5 | hgm_1.23.tar.gz |
126.7 KiB |
1.23 |
rolling linux/noble R-4.5 | hgm_1.23.tar.gz |
128.0 KiB |
1.23 |
latest source/ R- | hgm_1.23.tar.gz |
92.3 KiB |
1.23 |
latest linux/jammy R-4.5 | hgm_1.23.tar.gz |
126.7 KiB |
1.23 |
latest linux/noble R-4.5 | hgm_1.23.tar.gz |
128.0 KiB |
1.23 |
2026-04-23 source/ R- | hgm_1.23.tar.gz |
92.3 KiB |
1.23 |
2026-04-09 windows/windows R-4.5 | hgm_1.23.zip |
132.8 KiB |
1.23 |
2025-04-20 source/ R- | hgm_1.23.tar.gz |
92.3 KiB |